Overview of event
Please note there are two separate webinars on the same day relating to the same topic, hosted by different experts, to enable all time zones to participate. Link to later Webinar 2.
Developers have to make hundreds of design choices when creating Augmented Reality (AR) experiences: Is the system usable? Are the 3D interactions intuitive? One of the most important things developers can do is to evaluate their systems.
However, testing enterprise AR experiences with users presents challenges: the environment needs to replicate the real workplace as closely as possible, it can be difficult to measure what people are doing while performing a task, testers are likely to be separated from the users and unable to see exactly what the user sees in the experience, and not all of the results captured in a lab will translate to real world performance. These and other challenges require special methods for user evaluation.
In this webinar, Professor Mark Billinghurst will share how to design user evaluation experiences and the methods to measure user responses.
Key questions this webinar answers include:
- How to quickly design and set up the optimal testing environment?
- What different types of user evaluation can be done?
- How do you choose the “perfect” user for testing?
- What types of objective and subjective measures provide the best results?
- What are the emerging/new tools for user evaluation?
Participating in this webinar will provide attendees: –
- Background on AR user testing principles and best practices in workplace settings
- Guidance on how to design and conduct user evaluation studies
- Hardware and software tools for user testing
- Resources for further study on advanced user evaluation methods
Christine Perey, PEREY Research & Consulting
Professor Mark Billinghurst, thought leader in AR research, chair of the IEEE ISMAR steering committee, Professor at University of South Australia and the University of Auckland, Director of the Empathic Computing Laboratory, and a world leader in user evaluation methods.